{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: http://mirrors.cloud.aliyuncs.com/pypi/simple/\n",
      "Collecting xgboost\n",
      "  Downloading http://mirrors.cloud.aliyuncs.com/pypi/packages/2e/57/bf5026701c384decd2b995eb39d86587a103ba4eb26f8a9b1811db0896d3/xgboost-1.3.3-py3-none-manylinux2010_x86_64.whl (157.5 MB)\n",
      "\u001b[K     |████████████████████████████████| 157.5 MB 507 kB/s eta 0:00:01  | 11.8 MB 13.6 MB/s eta 0:00:11             | 17.3 MB 13.6 MB/s eta 0:00:11         | 28.5 MB 13.6 MB/s eta 0:00:1062.2 MB/s eta 0:00:06██████████▎                     | 50.6 MB 22.2 MB/s eta 0:00:05��████▊                     | 52.8 MB 957 kB/s eta 0:01:50��                    | 55.2 MB 957 kB/s eta 0:01:47                  | 58.7 MB 957 kB/s eta 0:01:447 kB/s eta 0:01:41██████████▌                 | 71.4 MB 275 kB/s eta 0:05:13            | 82.3 MB 456 kB/s eta 0:02:45�█▋             | 91.6 MB 504 kB/s eta 0:02:11  | 96.1 MB 504 kB/s eta 0:02:020 MB 504 kB/s eta 0:01:52MB 469 kB/s eta 0:01:44██████▊       | 121.7 MB 469 kB/s eta 0:01:17███████████████████▍     | 130.0 MB 492 kB/s eta 0:00:56��████████▌    | 135.1 MB 492 kB/s eta 0:00:46████████▌   | 140.2 MB 492 kB/s eta 0:00:36�███████████████████████████▋  | 145.8 MB 492 kB/s eta 0:00:244 MB 492 kB/s eta 0:00:15███████▌| 155.1 MB 492 kB/s eta 0:00:05\n",
      "\u001b[?25hRequirement already satisfied: numpy in /root/anaconda3/lib/python3.7/site-packages (from xgboost) (1.18.1)\n",
      "Requirement already satisfied: scipy in /root/anaconda3/lib/python3.7/site-packages (from xgboost) (1.4.1)\n",
      "Installing collected packages: xgboost\n",
      "Successfully installed xgboost-1.3.3\n"
     ]
    }
   ],
   "source": [
    "!pip install xgboost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cs-test.csv  cs-training.csv  Data Dictionary.xls  sampleEntry.csv\r\n"
     ]
    }
   ],
   "source": [
    "!ls ../../data/GiveMeSomeCredit/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'xxx/sampleEntry.csv'"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_path('sampleEntry.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
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